Data Architect OCP (Openshift) | IAM Data Modernization

Indent :PSL216927_1-26-1Role : Data Architect – OCP (OpenShift) | IAM Data ModernizationLocation : Dallas, TX / Charlotte, NC (Hybrid – 3 days office)Rate: $85/hr to $90/hrProject/ProgramIdentity & Access Management (IAM) Data Modernization Migration of an on-premises SQL data warehouse to a modern enterprise Data Lake platform, enabling analytics and GenAI use cases. The platform leverages PySpark-based processing, CI/CD pipelines, and containerized deployments on OpenShift (OCP), with GCP as a preferred cloud platform, to deliver scalable, secure, and high-performance data solutionsAbout Program/Project The IAM Data Modernization program focuses on transforming legacy data platforms into a scalable and cloud-compatible architecture.Key Highlights:

• Integration Scope: 30+ source systems with multiple downstream integrations [
• Capabilities: Metrics, reporting, advanced analytics, and GenAI use cases (NL querying, summarisation, cross-domain insights)
• Benefits:
  • Scalable and resilient data platform
  • High-performance semantic and analytics layer
  • Single source of truth for enterprise-wide reporting and analytics

Role Summary We are looking for a Data Architect with strong expertise in OpenShift (OCP), PySpark, and CI/CD pipelines to design and govern scalable data platforms. The role requires defining end-to-end data architecture, containerised deployment patterns, orchestration strategies (Airflow/Autosys), and platform standards, along with hands-on involvement in implementation.Key ResponsibilitiesData Architecture & Platform Design

• Define enterprise data architecture for IAM data lake and analytics platform
• Design scalable, modular, and containerised data pipeline architectures on OCP
• Establish data models, schema governance, and data lifecycle strategies
• Define best practices for data partitioning, performance optimisation, and cost efficiency

OpenShift (OCP) & Platform Engineering

• Architect and govern containerised data workloads on OpenShift (OCP)
• Define standards for deployment, scaling, and workload isolation
• Collaborate with DevOps teams for platform engineering and infrastructure alignment

Big Data & Processing (PySpark Focus)

• Define architecture for PySpark-based batch and near real-time processing pipelines
• Provide guidance on distributed processing design, optimisation, and performance tuning
• Establish reusable frameworks for ETL/ELT processing

Data Ingestion & Orchestration

• Architect data ingestion frameworks (batch, streaming, CDC)
• Define orchestration strategies using Airflow / Autosys
• Implement standards for retry, backfills, dependency management, and error handling

DevOps / CI-CD

• Define and oversee CI/CD strategy for data and platform deployments
• Enable automation of build, test, and deployment processes
• Ensure integration of CI/CD pipelines with OCP-based environments

Cloud & Data Platforms (Preferred)

• Provide architecture guidance for GCP-based data platforms (preferred, not mandatory)
• Define integration patterns for cloud-native and on-premise hybrid environments
• Guide teams on cloud migration strategies and modern data platform adoption

Data Governance, Quality & Observability

• Define frameworks for:
  • Data quality, validation, and lineage
  • Metadata management and cataloguing
• Establish monitoring, logging, alerting, and SLOs for platform reliability
• Ensure compliance with data security and audit requirements

Stakeholder Collaboration

• Work closely with client architects, IAM teams, and business stakeholders
• Translate business requirements into scalable technical architecture
• Provide architectural guidance and mentorship to engineering teams

Required SkillsCore Skills (Must Have)

• Strong experience in:
  • OpenShift (OCP) / Kubernetes-based platforms
  • PySpark / Spark ecosystem
  • CI/CD implementation for data platforms
  • Airflow / Autosys orchestration tools
• Solid understanding of:
  • Data lake architectures (layered models)
  • ETL/ELT design patterns
  • Distributed data processing concepts

Data Engineering & Storage

• Expertise in:
  • Data formats: Parquet, ORC, Avro
  • Partitioning and performance tuning
  • Large-scale data modelling for analytics

Cloud (Preferred – Not Mandatory)

• Experience with Google Cloud Platform (GCP) (preferred)
• Exposure to services like BigQuery, Dataproc, Dataflow, GCS is a plus

Observability & Reliability

• Experience defining:
  • Monitoring, logging, alerting frameworks
  • Dashboards, SLOs, and operational runbooks

Good to Have

• Experience with IAM domain / cybersecurity data
• Understanding of data security and access control frameworks
• Exposure to GenAI-enabled data platforms
• Experience in Agile delivery and team leadership

Qualifications

• Experience:
  • 10–14+ years in Data Architecture / Data Engineering
  • Strong experience in OCP, PySpark, CI/CD, and orchestration frameworks
  • Prior experience in data modernisation / migration programs
• Education: Bachelor's/Master's in Computer Science, Information Systems, or equivalent
• Certifications (Preferred):
  • OpenShift / Kubernetes certifications
  • GCP certifications (preferred, not mandatory)

DISCLAIMER========== This e-mail may contain privileged and confidential information which is the property of Persistent Systems Ltd. It is intended only for the use of the individual or entity to which it is addressed. If you are not the intended recipient, you are not authorized to read, retain, copy, print, distribute or use this message. If you have received this communication in error, please notify the sender and delete all copies of this message. Persistent Systems Ltd. does not accept any liability for virus infected mails.